This RediSearch page refers to 5 scoring models listed below.
We are using MongoDB as our primary store, but using RediSearch for faster cached queries. We would like the same result for each.
Does one of the scoring models listed below for RedisSearch match the one in MongoDB? Do they both use Lucene under the covers?
Scoring model ¶ RediSearch comes with a few very basic scoring functions to evaluate document relevance. They are all based on document scores and term frequency. This is regardless of the ability to use sortable fields (see below). Scoring functions are specified by adding the SCORER {scorer_name} argument to a search request.
If you prefer a custom scoring function, it is possible to add more functions using the Extension API .
These are the pre-bundled scoring functions available in RediSearch:
TFIDF (Default)
Basic TF-IDF scoring with document score and proximity boosting factored in.
TFIDF.DOCNORM Identical to the default TFIDF scorer, with one important distinction:
BM25
A variation on the basic TF-IDF scorer, see this Wikipedia article for more info .
DISMAX
A simple scorer that sums up the frequencies of the matched terms; in the case of union clauses, it will give the maximum value of those matches.
DOCSCORE
A scoring function that just returns the priory score of the document without applying any calculations to it. Since document scores can be updated, this can be useful if you'd like to use an external score and nothing further.
